Because a model is only an approximation of reality, the sensitivity of the solution to changes in the model and input data is a very important part of analyzing the results.
This type of analysis is called sensitivity analysis or postoptimality analysis.
It determines how much the solution will change if there were changes in the model or the input data.
When the solution is sensitive to changes in the input data and the model specification, additional testing should be performed to make sure that the model and input data are accurate and valid.
If the model or data are wrong, the solution could be wrong, resulting in financial losses or reduced profits.